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OntoBayes: An Ontology-Driven Uncertainty Model

CIMCA '05: Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06), : 457--463, 2005.
Authors: Yi Yang and Jacques Calmet
URL: http://portal.acm.org/citation.cfm?id=1135162
extra URLs: ieeexplore (fulltext) http://dblp.uni-trier.de/db/conf/cimca/cimca2005-1.html#YangC05
Description: OntoBayes
Tags: 2008-01-18 av:attached av:paper imported ontobayes proj:o4p toread
Abstract: This paper describes an ontology-driven model, which integrates Bayesian Networks (BN) into the Ontology Web Language (OWL) to preserve the advantages of both. This model makes use of probability and dependency-annotated OWL to represent uncertain information in BN structures. These extensions enhance knowledge representation in OWL and enable agents to act under uncertainty and complex structured open environments at the same time. This paper presents the underlying principles and scratches the surface of the decision theoretic agent system design based on "OntoBayes".
| URL | BibTeX  
@inproceedings{Yang2005,
title = {OntoBayes: An Ontology-Driven Uncertainty Model},
address = {Washington, DC, USA},
author = {Yi Yang and Jacques Calmet},
booktitle = {CIMCA '05: Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06)},
pages = {457--463},
publisher = {IEEE Computer Society},
url = {http://portal.acm.org/citation.cfm?id=1135162},
year = {2005},
description = {OntoBayes},
abstract = {This paper describes an ontology-driven model, which integrates Bayesian Networks (BN) into the Ontology Web Language (OWL) to preserve the advantages of both. This model makes use of probability and dependency-annotated OWL to represent uncertain information in BN structures. These extensions enhance knowledge representation in OWL and enable agents to act under uncertainty and complex structured open environments at the same time. This paper presents the underlying principles and scratches the surface of the decision theoretic agent system design based on "OntoBayes".},
isbn = {0-7695-2504-0-01},
keywords = {2008-01-18 av:attached av:paper imported ontobayes proj:o4p toread }
}